A study on data-driven identification and representation of nonlinear dynamical systems with a physics-integrated deep learning approach: Koopman operators and nonlinear normal modes. - Abdolvahhab Rostamijavanani; Shanwu Li; Yongchao Yang (Commun. Nonlinear Sci. Numer. Simul., 2023)

Data-driven Modeling of Parameterized Nonlinear Fluid Dynamical Systems with a Dynamics-embedded Conditional Generative Adversarial Network. - Abdolvahhab Rostamijavanani; Shanwu Li; Yongchao Yang (CoRR, 2024)

Data-driven identification of nonlinear dynamical systems with LSTM autoencoders and Normalizing Flows. - Abdolvahhab Rostamijavanani; Shanwu Li; Yongchao Yang (CoRR, 2025)

Data-driven Nonlinear Modal Analysis with Physics-constrained Deep Learning: Numerical and Experimental Study. - Abdolvahhab Rostamijavanani; Shanwu Li; Yongchao Yang (CoRR, 2025)